1. Field of the Invention
The present invention relates to electronic imaging devices. More specifically, the invention provides an areal active pixel image sensor for hyper-spectral imaging.
2. Description of Related Arts
FIG. A illustrates a hyper-spectral imaging environment 1 wherein a prism 2 is used to separate a broadband light image 10 into a hyper-spectral light image 11 having numerous wavelength separated components: narrowband light image at λa 11a, narrowband light image at λb 11b, . . . , narrowband light image at λf 11f. Equivalently although not shown here, other means such as a grating structure could be used to effect the spectral wavelength separation as well. The hyper-spectral light image 11 is then focused onto an areal image sensor 5 having imager row-1 5a, imager row-2 5b, . . . , imager row-M 5f corresponding to the numerous wavelength separated components 11a-11f and converting them into output electrical image signals with an overall photoelectric signal gain (GOA) for later analysis. In general, the GOA of an image sensor is defined as the following ratio:                output image signal voltage/incoming image light exposure energy.        
As an illustrated example, narrowband light image at λa 11a might correspond to a wavelength of 400 nanometer (nm), narrowband light image at λb 11b might correspond to a wavelength of 401 nm and narrowband light image at λf 11f might correspond to a wavelength of 900 nm. While a conventional areal image sensor implements a uniform GOA for all its sensor pixels, such traditional implementation will result in substantial image signal distortion when applied to the hyper-spectral imaging environment 1. This image signal distortion is rooted in a non-uniform (non-flat) spectral response of practically all photoelectric sensor elements of which a silicon spectral responsivity 15 is qualitatively illustrated in FIG. B. The Y-axis is spectral responsivity in ampere/watt while the X-axis is incoming light wavelength in nm. Thus, as a single cited example, the spectral responsivity near 800 nm is substantially higher than that near 500 nm. More quantitatively, the silicon spectral response variation is close to 5 times at wavelengths of higher responsivity than those at lower responsivity. To correct for this spectral responsivity rooted image signal distortion, post-imager software data compensation has been used in the past. As the post-imager software data compensation normally consumes significant power and energy, it is undesirable in sensitive applications such as satellite. A solution is desired for hyper-spectral imaging that preserves high signal fidelity, is compact and energy efficient.